2020
DOI: 10.1002/hyp.13735
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Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model

Abstract: The spatial variability of snow water equivalent (SWE) can exert a strong influence on the timing and magnitude of snowmelt delivery to a watershed. Therefore, the representation of sub-grid or sub-watershed snow variability in hydrologic models is important for accurately simulating snowmelt dynamics and runoff response. The U.S. Geological Survey National Hydrologic Model infrastructure with the precipitation-runoff modelling system (NHM-PRMS) represents the sub-grid variability of SWE with snow depletion cu… Show more

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Cited by 16 publications
(16 citation statements)
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“…SP was determined as the fraction of the MODIS 8‐Day images with snow present from January 1 to July 3, a period that 'brackets the extent of peak snow accumulation to complete snow ablation in most parts of the western United States' (Moore et al, 2015). We did not use any fractional snow‐covered area products (fSCA) because SP integrates snow cover over space (watershed area) and time; at these aggregated scales, previous analyses successfully related the MODIS 8‐day binary maximum snow‐covered extent to streamflow responses (Eurich et al, 2021; Hammond et al, 2018; Sexstone et al, 2020).…”
Section: Methodsmentioning
confidence: 99%
“…SP was determined as the fraction of the MODIS 8‐Day images with snow present from January 1 to July 3, a period that 'brackets the extent of peak snow accumulation to complete snow ablation in most parts of the western United States' (Moore et al, 2015). We did not use any fractional snow‐covered area products (fSCA) because SP integrates snow cover over space (watershed area) and time; at these aggregated scales, previous analyses successfully related the MODIS 8‐day binary maximum snow‐covered extent to streamflow responses (Eurich et al, 2021; Hammond et al, 2018; Sexstone et al, 2020).…”
Section: Methodsmentioning
confidence: 99%
“…Furthermore, previous work, primarily focused on non-forested areas (Brauchli et al, 2017;Luce et al, 1998;Sexstone et al, 2020;Seyfried & Wilcox, 1995), has shown that improved representation of snow heterogeneity increases modelled late-season streamflow. However, previous studies have not documented how a finer-scale representation of forest-snow interactions impacts basin-scale streamflow and whether that impact varies across regions with different climates and different forest cover.…”
Section: Introductionmentioning
confidence: 99%
“…For instance, prior studies have shown that at coarser spatial scales, models that use bulk canopy metrics and do not account for subgrid snow cover have a different net energy balance and snow melt rate than those at very high resolution (e.g., 1 m; Broxton et al, 2015; Mazzotti et al, 2020, 2021). Furthermore, previous work, primarily focused on non‐forested areas (Brauchli et al, 2017; Luce et al, 1998; Lundquist et al, 2005; Lundquist & Dettinger, 2005; Sexstone et al, 2020; Seyfried & Wilcox, 1995), has shown that improved representation of snow heterogeneity increases modelled late‐season streamflow. However, previous studies have not documented how a finer‐scale representation of forest‐snow interactions impacts basin‐scale streamflow and whether that impact varies across regions with different climates and different forest cover.…”
Section: Introductionmentioning
confidence: 99%
“…The low-to-no snow percentile-based definition is chosen based partly on the success of the Western US Drought Monitor's ability to highlight impactful water stress in the landscape (Svoboda et al, 2002;Huning & AghaKouchak, 2020b) and, more specifically, based on recent research which shows that runoff is reduced and consistently more constrained in portions of the western US when peak SWE approaches conditions of low-to-no snow (Sexstone et al, 2020;Hatchett et al, 2021).…”
Section: Mountain Definitionmentioning
confidence: 99%